A modeling framework for control of nonpoint source pollution and evaluation of best management practices for identification of critical source areas

Abstract This paper presents a modeling framework for nonpoint source (NPS) pollution control which involves the use of the MapShed hydrological model and the Water Quality Analysis Simulation Program (WASP8) to identify critical source areas (CSAs) for improving in-stream water quality at the watershed scale based on the efficiencies of agricultural best management practices (BMPs) for NPS load reductions. The study area is the coastal watershed of the Lower Aksu Stream in the south of Turkey. Extensive data collection facilitated model calibration, validation, and scenario analyses. There was a good agreement between the model predictions and measurements related to flow rate and water quality parameters. The most effective scenario (S3) combining BMPs for agriculture, pastureland, and animal waste management achieved significant annual load reductions: approximately 40% for total nitrogen (TN) and 25% for total phosphorus (TP). Two sub-watersheds were defined as the CSAs based on the contributions to total NPS pollution loads and load reductions by the investigated BMPs. Pastureland and animal waste management practices (S1 Scenario) were most effective in sub-watershed 5 with contributions of approximately 32% for both TN and TP annual load reductions. Scenario S2 (agricultural waste management) and Scenario S3 were most successful in sub-watershed 8 with contributions of 30.3% and 27.3% for TN and 35.7% and 28.7% for TP annual load reductions, respectively. The identification of CSAs enhances the effectiveness of BMPs for NPS pollution control.